Interference Cancellation for Downlink MU-MIMO

Slides:



Advertisements
Similar presentations
Doc.: IEEE /037r1 Submission March 2001 Khaled Turki et. al,Texas InstrumentsSlide 1 Simulation Results for p-DCF, v-DCF and Legacy DCF Khaled.
Advertisements

VHT-SIG-A and VHT-SIG-B Field Structure
Doc.: IEEE /0338r1 Submission March 2012 Hung-Yu Wei, National Taiwan UniversitySlide 1 DeepSleep: Power Saving Mode to Support a Large Number.
Doc.: IEEE /1392r0 Submission November 12, 2008 De Vegt (Qualcomm)Slide 1 Inputs for a VHT Selection Procedure Date: Authors:
Doc.: IEEE /301R0 Submission May 2002 Terry Cole, AMDSlide 1 A More Efficient Protection Mechanism Terry Cole AMD Fellow +1.
Doc.:IEEE /1275r0 Submission Laurent Cariou Nov, 2010 Slide 1 Complexity reduction for time domain H matrix feedback Authors: Date:
Submission Page 1 January 2002 doc.: IEEE 802.RR-02/018A-d1 Andrew Myles, Cisco Systems Report of ad hoc group relating to DFS and JPT5G proposal Andrew.
April 2013 doc.: IEEE Nov 2013 Dense Apartment Complex Capacity Improvements with Channel selection and Dynamic Sensitivity Control Date:
MIMO Broadcast Scheduling with Limited Feedback Student: ( ) Director: 2008/10/2 1 Communication Signal Processing Lab.
PHY Abstraction for TGax System Level Simulations
Doc.:IEEE /223r1 Submission March 2002 J. del Prado and S. Choi, Philips Slide 1 CC/RR Performance Evaluation - Revisited Javier del Prado and.
Doc.: IEEE /1062r2 Submission Zhendong Luo, CATR September 2010 RF Feasibility of 120 MHz Channelization for China Date: Authors: Slide.
Doc.: IEEE /0668r7 SubmissionMatt Fischer, Broadcom TX Mask Shoulders vis-à-vis ACI Date: Authors: May 2011 Slide 1.
Doc.: IEEE /1355r2 11ah Submission Date: Authors: Nov 2012 James Wang, MediaTek Slide 1.
Submission doc.: IEEE 11-14/0868r0 July 2014 Johan Söder, Ericsson ABSlide 1 UL & DL DSC and TPC MAC simulations Date: Authors:
GroupID Concept for Downlink MU-MIMO Transmission
Submission doc.: IEEE 11-14/0353r0 March 2014 Dongguk Lim, LG ElectronicsSlide 1 Suggestion on PHY Abstraction for Evaluation Methodology Date:
Doc.: IEEE / hew Submission March 2014 Raja Banerjea, CSRSlide 1 A Simplified Simultaneous Transmit and Receive Mechanism Date:
Doc.: IEEE /0839r0 Submission Slide 1S. Abraham, Qualcomm Inc. July 2010 DL MU-MIMO performance with QoS traffic and OBSS.
Doc.: IEEE /0018r0 Submission May 2004 Steve Shellhammer, Intel CorporationSlide 1 IEEE Wireless Coexistence TAG Steve Shellhammer
Doc.: IEEE /1294r0 Submission September 2011 Rolf de Vegt, QualcommSlide 1 Spec Framework Text for.11ah Bandwidth Modes Date: Authors:
Doc.: IEEE /0612r0 Submission May 2007 H. Zhang., et al.Slide 1 Comment Resolution on TX Beamforming CSI/Steering Feedback Quantization Bitwidth.
Submission March 2012 doc.: IEEE Slide 1 SINR and Inter-STA Interference Indication Feedback in DL MU-MIMO Date: Authors:
Doc.: IEEE / 0052r0 Submission January 2011 Slide 1 Max Nss for SU BF Date: Authors: Sameer Vermani, Qualcomm.
Doc.: IEEE /0324r0 Submission Slide 1Michelle Gong, Intel March 2010 DL MU MIMO Error Handling and Simulation Results Date: Authors:
Doc.: IEEE /0567r0 Submission Slide 1Michelle Gong, Intel May 2010 DL MU MIMO Analysis and OBSS Simulation Results Date: Authors:
Doc.: IEEE /0371r0 Submission March 2012 Ron Porat, Broadcom BF Feedback and Protocol Date: Authors: Slide 1.
Doc.: IEEE /0373r0 Submission March 2012 Ron Porat, Broadcom BF Frame Format Date: Authors: Slide 1.
Doc.: IEEE /0782r0 Submission July 2010 Daewon Lee, LG ElectronicsSlide 1 STA MU-MIMO Group Management Signaling Design Date: Authors:
Doc.: IEEE /0783r0 Submission July 2010 Daewon Lee, LG ElectronicsSlide 1 MU-MIMO support for BSS load balancing Date: Authors:
Doc.: IEEE /1234r0 Submission November 2009 Sameer Vermani, QualcommSlide 1 Interference Cancellation for Downlink MU-MIMO Date: Authors:
GroupID Concept for Downlink MU-MIMO Transmission
Doc.: IEEE /1123r0 Submission September 2010 Zhu/Kim et al 1 Date: Authors: [TXOP Sharing for DL MU-MIMO Support]
Slide 1 doc.: IEEE /1092r0 Submission Simone Merlin, Qualcomm Incorporated September 2010 Slide 1 ACK Protocol and Backoff Procedure for MU-MIMO.
Doc.: IEEE /0606r1 Submission Uplink Channel Access Date: Authors: May 2012 Minyoung Park, Intel Corp.Slide 1.
Submission doc.: IEEE 11-13/1440r0 November 2013 Clayton Shepard, Rice UniversitySlide 1 Argos | Practical Massive-MIMO Date: Authors:
Submission doc.: IEEE /0148r0 Nokia Internal Use Only January 2012 Chittabrata Ghosh, Nokia Slide 1 Date: Authors: Uplink Throughput.
Submission doc.: IEEE /1436r0 November 2014 Interdigital CommunicationsSlide 1 Overhead Analysis for Simultaneous Downlink Transmissions Date:
Submission doc.: IEEE /1186r2 September 2014 Pengfei Xia, Interdigital CommunicationsSlide 1 Comparisons of Simultaneous Downlink Transmissions.
Cyclic Shift Diversity Design for IEEE aj (45GHz)
Doc.: IEEE /0044r0 Submission Proposed Changes to Simulation Scenario Date: 2015/01/12 Takeshi Itagaki, Sony CorporationSlide 1 Authors: January.
Doc.: IEEE /0802r0 Submission July 2010 VHT-LTF sequence for 80 MHz Date: Authors: Sameer Vermani, QualcommSlide 1.
Doc.: IEEE /1420r1Nov 2014 Submission Po-Kai Huang (Intel) Slide 1 The Impact of Preamble Error on MAC System Performance Date: NameAffiliationsAddressPhone .
Doc.: IEEE /0538r0 Submission May 2009 Eldad Perahia, Intel CorporationSlide 1 Investigation into the n Doppler Model Date: Authors:
Doc.: IEEE /0330r2 SubmissionSameer Vermani, QualcommSlide 1 PHY Abstraction Date: Authors: March 2014.
Submission doc.: IEEE /0868r0 July 2015 Hakan Persson, Ericsson ABSlide 1 Impact of Frequency Selective Scheduling Feedback for OFDMA Date:
Doc.: ax Submission Sept 2014 Slide 1 Effect of CCA in residential scenario part 2 Date: Authors:
Doc.: ax Submission July 2014 Slide 1 Proposed Calibration For MAC simulator Date: Authors:
Doc.: IEEE /0493r0 Submission May 2010 Changsoon Choi, IHP microelectronicsSlide 1 Beamforming training for IEEE ad Date: Authors:
Doc.: IEEE /1288r1 Submission November 2010 Sameer Vermani, QualcommSlide 1 Frame Format for GroupID Management Date: Authors:
Doc.: IEEE /0161r1 Submission doc.: IEEE /0087r0 January 2010 R. Kudo, K. Ishihara and Y. Takatori (NTT) Slide 1 Measured Channel Variation.
Doc.: IEEE /0307r0 Submission January 2014 Nihar Jindal, Broadcom PHY Calibration Results Date: Authors: Slide 1.
Submission doc: IEEE /0807r0 July 2010 R. Kudo et al., NTT Slide 1 PHY Abstraction for MU-MIMO Date: Authors: Name AffiliationsAddressPhone .
Doc.: IEEE /0889r3 Submission June 2014 Nihar Jindal, Broadcom Performance Gains from CCA Optimization Date: Authors: Slide 1.
PHY Abstraction for MU-MIMO in TGac
Implicit Sounding for HE WLAN
Maximum Tone Grouping Size for ax Feedback
Maximum Tone Grouping Size for ax Feedback
Maximum Tone Grouping Size for ax Feedback
Multi-User MIMO Channel Measurements
Heterogenous per-Client Doppler in MU-MIMO Scenarios
Channel Dimension Reduction in MU Operation
Joint Processing MU-MIMO
Initial Distributed MU-MIMO Simulations
Reducing Channel Dimension in MU-MIMO CSI Feedback
Reducing Channel Dimension in MU-MIMO Explicit Feedback Operation
Strawmodel ac Specification Framework
Joint Transmissions: Backhaul and Gain State Issues
Comparison of Coordinated BF and Nulling with JT
Presentation transcript:

Interference Cancellation for Downlink MU-MIMO November 2009 doc.: IEEE 802.11-09/1234r0doc.: IEEE 802.11-yy/xxxxr0 doc.: IEEE 802.11-yy/xxxxr0 March 2010 Interference Cancellation for Downlink MU-MIMO Date: 2010-03-15 Authors: Sameer Vermani, Qualcomm Sameer Vermani, Qualcomm

doc.: IEEE 802.11-09/1234r0doc.: IEEE 802.11-yy/xxxxr0 November 2009 doc.: IEEE 802.11-09/1234r0doc.: IEEE 802.11-yy/xxxxr0 doc.: IEEE 802.11-yy/xxxxr0 March 2010 Abstract Downlink (DL) Multi-user (MU) MIMO is identified as a key technology to improve the overall network performance In 09/1234r0 we showed that : Interference Cancellation (IC) at the STA makes downlink (DL) MU-MIMO more robust To support Interference Cancellation in DL MU-MIMO at the STA: AP must transmit enough LTFs to enable channel estimation for the total number of spatial streams in the DL We call this mode of LTF transmission the ‘Resolvable LTF’ mode AP must signal to each STA which spatial streams are meant for it This document is a review of IC concept in 09/1234r0 with an additional strawpoll at the end Sameer Vermani, Qualcomm Sameer Vermani, Qualcomm

March 2010 Outline Introduction Interference Cancellation Receive processing Sources of CSI Error at AP Simulation results for 40MHz and reasonable product configurations AP with 4Tx; Clients have 2 Rx AP with 8Tx; Clients have 3 Rx Conclusions Straw poll Sameer Vermani, Qualcomm

Introduction to Interference Cancellation March 2010 Introduction to Interference Cancellation In DL MU-MIMO, clients can have more receive (Rx) antennas than the number of spatial streams they receive The additional antennas can be used for Interference Cancellation (IC) / Interference Suppression Particularly useful when precoding is imperfect due to errors in the CSI available at the AP This calls for a DL MU-MIMO preamble design that can support IC Each client should receive as many LTFs as needed to train the total number of spatial streams in the DL Each client should know which spatial streams are meant for it Sameer Vermani, Qualcomm

Receive MMSE for Interference Suppression March 2010 Receive MMSE for Interference Suppression For instance, consider a 4-antenna AP transmitting 1 ss each to 4 STAs each with 2 Rx antennas, the Rx signal at 8 Rx antennas is given by: The equivalent precoded channel is Hequiv = H8x4W4x4 The first two rows of Hequiv is the channel seen by STA1; H1 = Hequiv(1:2,:) STA1 can do the following MMSE processing to reduce the interference from other STAs: where the first element of x1 gives the estimate of the symbol for STA1 and 12 is the noise variance at STA1 Sameer Vermani, Qualcomm

Sources of CSI Errors at AP March 2010 Sources of CSI Errors at AP Pathloss to the STA or the amount of quantization in the CSI feedback report The channel estimation SNR or quantization level is fundamental to the accuracy of CSI Time variations in the channel A non-zero time interval between CSI feedback and DL MU-MIMO transmission causes discrepancies between precoding weights and the actual channel Feedback delay of 20 ms results in an error floor of -25 dBc (assuming a coherence time of 800 ms) Modeled as two independent additive noise sources in the CSI CSI Feedback Delay Error Floor {-20, -25, -30} dBc Channel Estimation Error Floor (Pathloss dependent) At high SNRs, CSI feedback errors dominate and at low SNRs, pathloss errors dominate Sameer Vermani, Qualcomm

March 2010 Simulations Determine the gains of using MU-MIMO and Interference Cancellation (IC) We plot the 10 percentile and 50 percentile points from the CDF of the aggregate PHY throughput (measured at the AP) as a function of pathloss For comparison, we also plot the corresponding sequential beamforming (BF) data quantities SVD based transmission with equal MCS per spatial stream Data rates averaged across sequential transmissions to the clients Sameer Vermani, Qualcomm

Results for 4 antenna AP, Four clients each with 2 Rx, full loading March 2010 Results for 4 antenna AP, Four clients each with 2 Rx, full loading Sameer Vermani, Qualcomm

Simulation Parameters March 2010 Simulation Parameters AP with 4 Tx antennas transmitting at 24 dBm Noise floor of -89.9 dBm 4 STA with 2 Rx antenna each -35 dBc of TX distortion Equal Pathloss to each STA, varied from 70 to 95 dB Single SS per STA in the MU-MIMO case and 2 ss for Tx BF case TGac Channel Model D, NLOS Results for 200 channel realizations For MU-MIMO, MMSE precoding done to beamform the 1 ss of each STA to one of its antennas Two sources of CSI error at AP Channel estimation floor at client = -(Total Tx Power – Pathloss + 89.9 dBm (Thermal noise)) Feedback delay error = {-20, -25 ,-30} dBc Sameer Vermani, Qualcomm

4 antenna AP, Four 2 Rx clients, -20 dBc feedback error March 2010 4 antenna AP, Four 2 Rx clients, -20 dBc feedback error Eigen BF TDMA MU-MIMO w/o IC MU-MIMO with IC Eigen BF TDMA MU-MIMO w/o IC MU-MIMO with IC MU-MIMO with IC gives best performance Interference Cancellation improves performance for a poor CSI accuracy IC enables full loading Compare with slide 22 in Appendix, which shows the 3 ss results Performance better with 3 ss in the absence of IC Sameer Vermani, Qualcomm

4 antenna AP, Four 2 Rx clients, -25 dBc feedback error March 2010 4 antenna AP, Four 2 Rx clients, -25 dBc feedback error Eigen BF TDMA MU-MIMO w/o IC MU-MIMO with IC Eigen BF TDMA MU-MIMO w/o IC MU-MIMO with IC For all pathlosses between 70 and 95, MU-MIMO with IC gives substantial gains Sameer Vermani, Qualcomm

4 antenna AP, Four 2 Rx clients, -30 dBc feedback error March 2010 4 antenna AP, Four 2 Rx clients, -30 dBc feedback error Eigen BF TDMA MU-MIMO w/o IC MU-MIMO with IC Eigen BF TDMA MU-MIMO w/o IC MU-MIMO with IC For all pathlosses between 70 and 95, MU-MIMO with IC gives best performance Gains of IC reduce as CSI accuracy improves Sameer Vermani, Qualcomm

Results for 8 antenna AP, Three clients each with 3 Rx March 2010 Results for 8 antenna AP, Three clients each with 3 Rx Sameer Vermani, Qualcomm

Simulation Parameters March 2010 Simulation Parameters AP with 8 Tx antennas transmitting at 24 dBm Noise floor of -89.9 dBm 3 STA with 3 Rx antenna each -35 dBc of TX distortion Equal Pathloss to each STA, varied from 70 to 95 dB Two SS per STA in the MU-MIMO case and 3 ss for Tx BF case TGac Channel Model D, NLOS Results for 200 channel realizations For MU-MIMO, MMSE precoding done to beamform the 2 ss of each STA to two of its antennas Two sources of CSI error at AP Channel estimation floor at client = -(Total Tx Power – Pathloss + 89.9 dBm (Thermal noise)) Feedback delay error = {-20, -25 ,-30} dBc Sameer Vermani, Qualcomm

8 antenna AP, Three 3 Rx clients, -20 dBc feedback error March 2010 8 antenna AP, Three 3 Rx clients, -20 dBc feedback error MU-MIMO with IC gives best performance IC improves performance for a poor CSI accuracy Sameer Vermani, Qualcomm

8 antenna AP, Three 3 Rx clients, -25 dBc feedback error March 2010 8 antenna AP, Three 3 Rx clients, -25 dBc feedback error For all pathlosses between 70 and 95, MU-MIMO with IC gives best performance Sameer Vermani, Qualcomm

8 antenna AP, Three 3 Rx clients, -30 dBc feedback error March 2010 8 antenna AP, Three 3 Rx clients, -30 dBc feedback error Gains of IC reduce here Precoding is very good Sameer Vermani, Qualcomm

Conclusions IC makes MU-MIMO robust to poor CSI accuracy at the AP March 2010 Conclusions IC makes MU-MIMO robust to poor CSI accuracy at the AP Significantly improves PHY throughput Enables fully loaded MU-MIMO This calls for a DL MU-MIMO preamble design that can support IC AP must transmit enough LTFs to enable an STA to train the total number of spatial streams in the DL AP must signal to each STA which spatial streams are meant for it Sameer Vermani, Qualcomm

March 2010 Straw Poll Do you support the Interference Cancellation concept described in this document by inclusion of the following section and text in the Tgac spec framework document: “4.1 Resolvable LTFs for DL MU-MIMO In a DL MU-MIMO transmission, LTFs are considered “resolvable” when the AP transmits enough LTFs for an STA to estimate the channel to all spatial streams of every recipient STA. In order to enable interference cancellation at an STA during a DL MU-MIMO transmission, an AP may transmit the preamble using resolvable LTFs. ” Yes No Abstain Sameer Vermani, Qualcomm

March 2010 Appendix Sameer Vermani, Qualcomm

Methodology used to get to Data Rate CDFs March 2010 Methodology used to get to Data Rate CDFs For each spatial stream Calculate the post processing SINR on each tone Map the post processing SINR to capacity using log(1+SINR) Average the capacity across tones to get Cav Use Cav to calculate SINReff using Cav = log(1+ SINReff) Map the SINReff to a rate using the AWGN rate table This method is used in other WAN standards, e.g., 3GPP2 Sum the rate across all spatial streams for one channel realization to get to aggregate PHY throughput Do this for 200 channels to get to the CDF of aggregate PHY throughput Sameer Vermani, Qualcomm

4 antenna AP, Three 1x1 clients, -20 dB feedback error March 2010 4 antenna AP, Three 1x1 clients, -20 dB feedback error 70 75 80 85 90 95 100 200 300 400 500 600 700 800 Pathloss in dB PHY Rate in Mbps measured at AP Variation of 10 percentile PHY Rates with pathloss Eigen BF TDMA MU-MIMO w/o IC MU-MIMO with IC 70 75 80 85 90 95 100 200 300 400 500 600 700 800 Pathloss in dB PHY Rate in Mbps measured at AP Variation of 50 percentile PHY Rates with pathloss Eigen BF TDMA MU-MIMO w/o IC MU-MIMO with IC For all pathlosses between 70 and 95, MU-MIMO gives substantial gains IC curve lies on top of MU-MIMO w/o IC In absence of IC, 4 SS MU-MIMO performs worse than 3 SS MU-MIMO Compare green curve of this slide with blue curve of slide 10 Better to transmit at 75% loading in the absence of extra antenna at the STAs Scheduler decision Sameer Vermani, Qualcomm